MLS-C01 Practice Question: Machine Learning Implementation and Operations
A media company uses SageMaker to deploy a real-time inference endpoint for content recommendation. The model is a PyTorch model that uses GPU. The endpoint is deployed with an ml.p3.2xlarge instance. Over time, the endpoint's latency increases significantly during peak hours. The company has enabled auto scaling based on CPU utilization. However, the latency spikes occur even when CPU utilization is low. The model is stateless and the inference code is efficient. What is the MOST likely cause of the latency spikes?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Auto scaling is configured based on CPU utilization, but the bottleneck is GPU utilization
The model runs on GPU, so the bottleneck is GPU utilization, not CPU. Auto scaling based on CPU utilization does not help when the GPU is saturated. The latency spikes during peak hours suggest that the GPU is overloaded, but auto scaling is not triggered because CPU utilization remains low.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model uses stateful processing that accumulates requests
Why it's wrong here
Model is stateless.
- ✓
Auto scaling is configured based on CPU utilization, but the bottleneck is GPU utilization
Why this is correct
GPU metrics should be used for auto scaling.
- ✗
The inference container has a memory leak that causes gradual slowdown
Why it's wrong here
The model is stateless and efficient.
- ✗
The instance type is too small for the model
Why it's wrong here
Instance was chosen for GPU, but scaling is the issue.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.